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A semi-analytical method for two-dimensional sound propagation in subsonic parallel mean flow.

Jinxiao Li1, Haijun Wu1, Changjiang Liao2

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A new method, the linear-velocity-profile fast field program (LFFP), accurately predicts 2D sound fields in flows. It improves precision and efficiency, especially with high velocity gradients, outperforming traditional methods.

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Area of Science:

  • Acoustics
  • Fluid Dynamics
  • Computational Physics

Background:

  • Predicting sound propagation in moving fluids is crucial for applications like noise control and sonar.
  • Traditional Fast Field Program (FFP) methods face challenges with high velocity gradients in ambient flows.
  • Accurate modeling of sound fields in complex flow environments remains an active research area.

Purpose of the Study:

  • To introduce a novel semi-analytical method, the linear-velocity-profile fast field program (LFFP), for enhanced prediction of 2D sound fields.
  • To improve computational efficiency and accuracy of sound field predictions in parallel mean flows, particularly those with significant velocity gradients.
  • To provide a systematic mathematical explanation for the improved accuracy of LFFP compared to traditional FFP.

Main Methods:

  • Developed the linear-velocity-profile fast field program (LFFP) by integrating linear velocity layering into the Fast Field Program (FFP) framework.
  • Validated LFFP accuracy using a 2D jet case against the linearized Euler equation in the frequency domain.
  • Employed residual analysis to investigate and explain the enhanced precision of LFFP in shear flow scenarios.

Main Results:

  • LFFP demonstrates superior accuracy and reduced computational cost compared to traditional FFP, especially in high-velocity gradient conditions.
  • Validation against the linearized Euler equation confirms the predictive capabilities of LFFP for 2D sound fields.
  • Identified the consideration of the second velocity gradient term in the Pridmore-Brown operator as key to LFFP's improved precision.

Conclusions:

  • The LFFP method offers a significant advancement in predicting 2D sound fields in parallel mean flows.
  • The developed multi-staircase layering model, based on residual analysis, further enhances computational efficiency for complex ambient environments.
  • LFFP provides a more accurate and efficient tool for acoustic modeling in dynamic fluid environments.